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108,45 €
+ 216 points
Description
Bayesian decision analysis supports principled decision making in complex domains. This textbook takes the reader from a formal analysis of simple decision problems to a careful analysis of the sometimes very complex and data rich structures confronted by practitioners. The book contains basic material on subjective probability theory and multi-attribute utility theory, event and decision trees, Bayesian networks, influence diagrams and causal Bayesian networks. The author demonstrates when and how the theory can be successfully applied to a given decision problem, how data can be sampled and expert judgements elicited to support this analysis, and when and how an effective Bayesian decision analysis can be implemented. Evolving from a third-year undergraduate course taught by the author over many years, all of the material in this book will be accessible to a student who has completed introductory courses in probability and mathematical statistics.
Spécifications
Parties prenantes
- Auteur(s) :
- Editeur:
Contenu
- Nombre de pages :
- 348
- Langue:
- Anglais
Caractéristiques
- EAN:
- 9780521764544
- Date de parution :
- 15-11-10
- Format:
- Livre relié
- Format numérique:
- Ongenaaid / garenloos gebonden
- Dimensions :
- 175 mm x 246 mm
- Poids :
- 816 g
